Dissociation of dimeric cis-9-octadecenoic acid in its pure liquid state as observed by near-infrared spectroscopic measurement

Iwahashi, Makio; Hachiya, Norihisa; Hayashi, Yoshinori; Matsuzawa, Hideyo; Suzuki, Masao; Fujimoto, Yasuhiko; Ozaki, Yukihiro

doi:10.1021/j100115a011

Cited by 54 publications

(60 citation statements)

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“…5,6 The dissociation of dimers of cis-9octadecenoic acid into monomeric species in its pure liquid form was investigated; the study showed that the dissociation occurs even at low temperatures and increases with increasing temperature. The molar absorption coefficient and the absorbance for the neat sample at various temperatures, T, produce the temperature dependence of the degree of dissociation, α, for dimeric cis-9-octadecenoic acid into monomers in the liquid state.…”

Section: Structure and Self-association Of Fatty Acids And Alcoholsmentioning

confidence: 99%

An Overview of Research and Development of near Infrared Spectroscopy in Japan

Iwamoto

Ozaki

1995

Journal of Near Infrared Spectroscopy

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This paper presents an overview of research and development of near infrared (NIR) spectroscopy in Japan. The application of NIR spectroscopy in Japan only stretches back to the early 1980s. Thus, the history is rather short, but progress in the research and development of NIR spectroscopy is extremely fast. The history and present status of NIR spectroscopy in Japan are described and a number of representative applications carried out in Japan are introduced.

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Section: Structure and Self-association Of Fatty Acids And Alcoholsmentioning

confidence: 99%

An Overview of Research and Development of near Infrared Spectroscopy in Japan

Iwamoto

Ozaki

1995

Journal of Near Infrared Spectroscopy

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“…12 The results with 5676 and 5790 cm -1 follow this structural change in the temperature range. For example, xc values estimated with 5676 and 5790 cm -1 agree with the structural changes of OA in both cases of LMedS and LS estimator.…”

Section: Curve Fitting With Simulated Data Setmentioning

confidence: 70%

Robust Curve Fitting Method for Optical Spectra by Least Median Squares (LMedS) Estimator with Particle Swarm Optimization (PSO)

et al. 2007

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Curve fitting is one of the most important methods to extract not only chemical but also biological information in perturbations. 1 By the assumption of proper model function, curve fitting enables one to describe detailed changes caused by perturbation. However, we sometimes experience difficulty in obtaining a desirable fit between observed data and a model function. One of the main reasons for this problem is that all fitting parameters are based on a least squares (LS) estimator. An LS estimator determines all parameters of a model function by minimizing sum of squared residuals between observed and predicted values. Such an estimator is strongly influenced by outliers in a data set. For example, LS estimator has a breakdown value of 0%, namely it is strongly influenced by even only one outlier in data. 2 It is not adequate to apply such curve fitting to a data set with strong noise. In the practice of curve fits for such data including noise, it is more desirable to obtain fitting parameters by some robust estimators that are less influenced by outliers. Therefore, we introduce a new technique for curve-fitting based on a robust estimator, least median squares (LMedS). The LMedS estimator is defined to be the parameter which minimizes the median of the squared residuals between observed and predicted values. The LMedS estimator has a remarkable tolerance toward outliers of 50% in a data set. 3,4 In spite of such theoretical advantage, it requires more computational complexity compared with the LS estimator. Generally, a Monte-Carlo type technique is used to obtain a satisfying approximation of the LMedS estimator because, so far, there are no straightforward formulas for the LMedS estimator. 6Such technique needs many iterations and computational complexity increase with the increase in the number of parameters in the model function. In this study, particle swarm optimization (PSO) is introduced to acquire the LMedS estimator for out curve fits. PSO, developed by Eberhart and Kennedy in 1995, is a stochastic search method inspired by the social behavior of bird flocking. Similar to the genetic algorithm (GA), PSO is a population-based optimization tool that searches for optima by updating generations. [5][6][7][8][9] However, unlike GA, 10 PSO includes no evolution operators such as crossover and mutation. Compared to GA, a remarkable advantage of PSO is that its algorithm is conceptually very simple, computation costs are low and few adjustable parameters are needed.The proposed robust curve fitting method is demonstrated with simulated data and temperature-dependent near-infrared (NIR) spectra of oleic acid (OA). The results show that the proposed method is more effective than a standard curve fit based on the LS estimator when the data set has high level noise. Theory LMedS estimatorWe are given a set of n observations in the plane (xi, yi), for i = 1, ... , n, and consider a linear regression model,LMedS can be defined as; A curve fitting technique for optical spectra based on a robust estimator, least ...

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“…polymers. [33][34][35][36][37][38][39][40][41][42][43] The reason why NIR spectroscopy is very useful for the studies of self-associated molecules is that the absorption bands in the NIR region (14,000-4000 cm -1 ) are mainly due to overtones and combinations associated with the groups having a hydrogen atom such as C-H, O-H and N-H. Anharmonicity of X-H bonds is very large and the fundamental modes of X-H stretching appear in the high frequency region of the IR spectra. Therefore, a NIR spectrum is, in general, very complicated but in some sense it enhances bands due to X-H groups.…”

Section: Two-dimensional Nir Correlation Spectroscopy Studies Of Tempmentioning

confidence: 99%

Potential of Generalised Two-Dimensional Correlation Spectroscopy in the near Infrared Region

Ozaki

Noda

1996

Journal of Near Infrared Spectroscopy

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This review demonstrates the potential of generalised two-dimensional (2D) correlation spectroscopy in the near infrared (NIR) region. Three examples of generalised 2D NIR correlation analysis, which are all concerned with the temperature-dependent spectral variations of self-associated molecules, are discussed in this paper. The first example presents the 2D correlation approach to the analysis of a set of NIR spectra of oleyl alcohol in the pure liquid state under temperature changes. The 2D NIR analysis enhances the spectral resolution and simplifies the spectra with overlapped bands. For example, it was found that a band at 7090 cm -1 , arising from the first overtone of an OH stretching mode of the monomeric alcohol, consists of two bands due to the rotational isomerism of the free OH group. The second example deals with the temperature-dependent NIR spectral changes of N-methylacetamide (NMA). The close-up view of 2D NIR correlation spectra of NMA, obtained at narrow spectral and temperature windows, enabled us to propose not only band assignments in the 6800-6050 cm -1 region, where the first overtones of stretching modes of free, free-end and hydrogen-bonded NH groups were expected to appear, but also a detailed mechanistic picture of the thermally-induced dissociation of NMA for each temperature range. A 2D NIR study of premelting behaviour and hydrogen bonds of Nylon 12 is discussed as the third example. The asynchronous 2D NIR correlation spectrum of Nylon 12 obtained from 30 to 150ºC in the 6900-6100 cm -1 region indicated that the amide group with a free carbonyl oxygen appears first and then the unassociated free amide and amide with free NH follow as the temperature is increased. The asynchronous spectrum in the 6000-5500 cm -1 region, where the first overtones of the CH 2 stretching modes are expected to appear, suggested that a substantial amount of disordered or dissociated components start appearing before the disappearance of more ordered components. It seemed that they appear as the premelting precursors (or even possibly as the indirect cause) to the precipitous decrease of the ordered components associated with the melting of Nylon 12 occurring at a much higher temperature.The basic concept of two-dimensional (2D) vibrational spectroscopy was introduced by one of the authors (Noda) in 1986. 1 It is somewhat analogous to that of the 2D technique employed in nuclear magnetic resonance (NMR). However, the specific experimental procedure developed for 2D infrared Y. Ozaki and I. Noda, J. Near Infrared Spectrosc. 4, 85-99 (1996) 85 © NIR Publications 1996, ISSN 0967-0335 (IR) spectroscopy is substantially different from that used in 2D NMR. The major obstacle is that vibrational relaxation rates (picosecond range) are many orders of magnitude faster than typical spin relaxation rates (microsecond range or even longer) encountered in NMR. Ordinary IR spectrometers cannot adequately provide the rapid excitation and detection of vibrational relaxation responses necessary in order to carry out s...

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Dissociation of dimeric cis-9-octadecenoic acid in its pure liquid state as observed by near-infrared spectroscopic measurement

Cited by 54 publications

References 1 publication

An Overview of Research and Development of near Infrared Spectroscopy in Japan

An Overview of Research and Development of near Infrared Spectroscopy in Japan

Robust Curve Fitting Method for Optical Spectra by Least Median Squares (LMedS) Estimator with Particle Swarm Optimization (PSO)

Potential of Generalised Two-Dimensional Correlation Spectroscopy in the near Infrared Region

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